health outcomes and reduce costs for chronically ill individuals. On one end of the spectrum are disease … supporting patient self-management. This qualitative review finds that carve-out disease management interventions that target … study design methodology limit quantitative analysis. More innovation and research are needed to understand how disease …

predict the disease before the actual symptoms are revealed in humans. By using data analytics algorithms one can easily … predict chronic diseases such as obesity, high/low Blood Pressure, diabetes, asthma, cardiopulmonary disorders. Because of an … handling health care data. For each chronic disease, diverse models, techniques, and algorithms are used for predicting and …

disability occurred because of chronic disease prevention efforts among the elderly. For this purpose we analyze data from the …, as reflected in decreased disease prevalence, was not responsible for advances made in elderly functioning between 1980 … disease management. Instead, these measured improvements in functioning may reflect environmental, technological, and …